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"Open Innovation" and "Triple Helix" Models of Innovation: Can Synergy in Innovation Systems Be Measured?
Loet Leydesdorff, Inga Ivanova
TL;DR
The paper asks how innovation ecosystems and knowledge-based economies can be understood and improved through differing social coordination mechanisms. It develops the Triple Helix as a model in which redundancy and multiple perspectives generate new options, while noting that its functions must be inferred rather than directly observed.
Problem
The paper examines how innovation ecosystems can be improved and how knowledge-based economies differ from political economies, including their relation to public R&D.
Method
The paper analyzes innovation ecosystems through social coordination mechanisms and differing perspectives associated with the Triple Helix.
Results
More redundancy reduces uncertainty and can be expressed in terms of negative amounts, while the Triple Helix provides a model of redundancies that make more and new options available.
Takeaways & Limitations
Redundancy enriches the innovation process by increasing the availability of new options.
Takeaways & Limitations
The Triple Helix functions are not directly observable and must be inferred from variations across its dimensions.
Abstract
from arXiv · showhide
The model of "Open Innovations" (OI) can be compared with the "Triple Helix of University-Industry-Government Relations" (TH) as attempts to find surplus value in bringing industrial innovation closer to public R&D. Whereas the firm is central in the model of OI, the TH adds multi-centeredness: in addition to firms, universities and (e.g., regional) governments can take leading roles in innovation eco-systems. In addition to the (transversal) technology transfer at each moment of time, one can focus on the dynamics in the feedback loops. Under specifiable conditions, feedback loops can be turned into feedforward ones that drive innovation eco-systems towards self-organization and the auto-catalytic generation of new options. The generation of options can be more important than historical realizations ("best practices") for the longer-term viability of knowledge-based innovation systems. A system without sufficient options, for example, is locked-in. The generation of redundancy -- the Triple Helix indicator -- can be used as a measure of unrealized but technologically feasible options given a historical configuration. Different coordination mechanisms (markets, policies, knowledge) provide different perspectives on the same information and thus generate redundancy. Increased redundancy not only stimulates innovation in an eco-system by reducing the prevailing uncertainty; it also enhances the synergy in and innovativeness of an innovation system.
Abstract
The paper focuses on innovation, redundancy, knowledge, code, and options.
- The paper identifies innovation, redundancy, knowledge, code, and options as its central keywords.
- Redundancy and options are presented as central concepts alongside innovation and knowledge.
- The paper also foregrounds code as a key concept in its analysis.
Introduction
The introduction compares Open Innovation, centered on firms using internal and external ideas, with the Triple Helix, which emphasizes university-industry-government relations and knowledge production. It frames innovation-system improvement as a problem of coordinating economic, scientific, political, and knowledge-based mechanisms beyond the market.
- Open Innovation treats firms as principal agents that use internal and external ideas and paths to market.
- The Triple Helix broadens the innovation infrastructure to university-industry-government relations and organized knowledge production.
- The introduction asks how innovation ecosystems can be improved through social coordination mechanisms that function beyond the market.
- A knowledge-based economy adds knowledge production as a third coordination mechanism to markets and political institutions.
- The introduction highlights weak technology-transfer and commercialization performance among most Dutch research universities outside technical universities and academic medical centers.
The neo-evolutionary turn of the TH
The neo-evolutionary Triple Helix shifts attention from fixed institutional relations toward interacting selection environments and their effects on variation, uncertainty, and system development. It treats innovation systems as layered, differentiated, and potentially subject to tensions between integration and differentiation and between local and global dimensions.
- The Triple Helix analyzes interactions among economic, scientific, and political selection environments rather than only bilateral institutional relations.
- Interactions among selection environments reduce uncertainty and require economic assumptions to be reformulated in a neo-evolutionary framework.
- Feedback and feedforward relations replace linear technology-push or demand-pull models as drivers of longer-term development.
- Triple Helix relations can be represented as triangles or overlapping institutional spheres, with intersections including funding, technology transfer, and strategic priority programs.
- Institutional relations tend to be sticky, producing tensions between integration and differentiation and between local and global dimensions.
Historical trajectories and evolutionary regimes
The paper’s historical and evolutionary perspective examines how technological trajectories and regimes reshape interactions among demand, supply, and technology. It emphasizes that established technologies or institutional arrangements can lock systems in and limit their ability to absorb new options.
- Demand, supply, and technological relations define three main functions whose interactions can generate a technological regime.
- The neo-evolutionary model studies interactions among selection environments rather than only networks of agents.
- Technological trajectories and emerging regimes can endogenously transform institutional relations through longitudinal selection mechanisms.
- Innovation-system trajectories depend partly on absorptive capacities on the demand side and the environment’s labor-force skill structure.
- Highly industrialized countries and regions may become locked into dominant technologies or institutional arrangements and lose flexibility to absorb new options.
Interactions among the helices
The Triple Helix models knowledge production, wealth generation, and normative control as distinct functions whose interactions can create self-organization rather than merely aggregate dyadic relations.
- The three TH functionalities are knowledge production, wealth generation, and normative control, associated primarily with academia, industry, and governance.
- The coordination mechanisms can be represented as orthogonal Cartesian axes, positioning agents and relations within a shared innovation-system space.
- The analysis shifts attention from individual firms to the knowledge-based reconstruction and transformation of relations among innovation agents.
- A three-dimensional TH can behave differently from three double helices because relations loop forward or backward, producing fruition or lock-in.
- Each party can catalyze or inhibit relations between the other two, making the system potentially auto-catalytic and self-organizing.
- Self-organization adds a global layer of expectations above local institutional organization, with expectations stimulating knowledge-production processes.
Measurement
The TH methodology operationalizes innovation systems through latent functional dimensions or observable firm distributions and applies these representations to measure synergy across national and regional systems.
- TH functionalities can be treated as abstract latent dimensions, while observable variables can represent units of analysis such as firms.
- National innovation systems have been modeled using firms’ geographical addresses, technological knowledge bases, and economic weights.
- The approach can compute mutual redundancy in three or four dimensions and has also been applied to supply, demand, and technological capabilities.
- The methodology decomposes national systems across countries and regions, with some analyses adding national-level contributions to regional sums.
- In Sweden, the knowledge-based economy is heavily concentrated in Stockholm, Gothenburg, and Malmö/Lund.
- Observed configurations differ across countries: German synergy is mainly located in Länder, while Italian differentiation primarily separates northern and southern areas.
Path-dependency, transition, regime change
Triple Helix dynamics are path-dependent and transitional, while changing configurations can generate new options and shift systems toward evolutionary self-organization.
- Communication direction creates asymmetries in triads, so different loop arrangements can produce different paths through the system.
- Triple Helix systems are path-dependent because returning to a previous state is not frictionless, leaving them in transition rather than equilibrium.
- Aggregated actions in one direction can rotate the structure, including the orientation of the knowledge-production axis.
- Historical organization and evolutionary self-organization remain simultaneously relevant and form a measurable variable that can be positive, negative, or zero.
- Redundancy equals the difference between maximum entropy and observed uncertainty, representing options specified by the system but not yet realized.
- Technological evolution can make historically impossible options feasible, while greater redundancy reduces uncertainty and may favor innovation-supporting niches.
The generation of redundancy in TH systems
The paper treats redundancy as surplus information generated by overlapping functional perspectives and uses mutual-information relations to measure self-organization in multidimensional systems.
- Redundancy is proposed as a way to add new options to a system through knowledge production across functional dimensions.
- Academic, industrial, and political perspectives can read the same events differently, with their overlaps interpreted as redundancy rather than mutual information.
- For two variables, overlapping value sets represent mutual information or transmission, providing the basis for correcting or interpreting overlap.
- The two-variable mutual redundancy is negative because positive transmission makes the redundancy equal to a negative amount of information, interpreted as reduced uncertainty.
- In systems with more than two dimensions, the resulting redundancy balances redundancy generation against historical uncertainty generation.
- A negative resulting R indicates predominance of self-organization, whereas a positive R indicates predominance of organization.
The multiplication of options in social systems
Adding communication channels changes a system’s carrying capacity from dependence on actors toward multiplication through interactions, expanding innovation options.
- The multiplication of options in social systems: New communication channels create options beyond existing physical constraints, as air transport across the Alps illustrates.The example contrasts roads and railways with a newly invented channel that is not constrained by ground conditions.
- The multiplication of options in social systems: The number of options is multiplied with each new channel rather than merely increased additively.This claim motivates the matrix-based formalization of network capacity.
- The multiplication of options in social systems: When communications are sparse, system capacity tracks the number of units, but increasing communications reduces that dependence on n in the product n x m.The text contrasts actor counts with communication infrastructure as determinants of capacity.
- The multiplication of options in social systems: Each additional communication dimension multiplies a system’s carrying capacity, allowing growth beyond limits based only on the number of actors.The formalization represents a network as an n x m matrix, where n counts units and m counts communications.
- The multiplication of options in social systems: Communication among differentiated codes can rapidly increase the number of innovation options.The model treats columns as differentiated communication channels whose addition expands available options.
Summary and conclusions
The Triple Helix extends Open Innovation by modeling multiple institutional roles, coded perspectives, and feedback mechanisms that generate and measure new innovation options. Its central claim is that redundancy across communication codes can reduce uncertainty and support innovation-system synergy.
- Summary and conclusions: The Triple Helix adds universities and governments to the firm-centered Open Innovation model, creating a multi-centered innovation system.These actors can take leading roles in innovation ecosystems and are specified as selection environments.
- Summary and conclusions: Different coded perspectives on innovation interact to shape the number of available options and reduce uncertainty.The paper treats these perspectives as supra-individual communication systems whose interaction can be modeled and analyzed.
- Summary and conclusions: Differentiation among communication codes can support cultural-technological evolution by shifting emphasis from historical organization toward evolutionary self-organization.The paper contrasts historical realizations with models and options generated within the knowledge base.
- Summary and conclusions: Triple-Helix models measure the efficiency of anticipatory mechanisms that can be exploited for technological development and innovation.The models provide options for simulation while evaluating anticipatory mechanisms.
- Summary and conclusions: Exchanges among partners with different institutional roles can generate redundancies that make more and new innovation options available.The paper links these exchanges to communication codes and knowledge-based interactions.
- Summary and conclusions: An additional feedback loop shifts coordination from politics and economics toward a system that also contains organized knowledge production.Knowledge production is presented as a third mechanism of social coordination alongside power and money.